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Data Science & Analytics
Alpaca
Alpaca is a US-headquartered, global leader in agent-first brokerage infrastructure for stocks, ETFs, options, crypto, fixed income and 24/5 trading, serving hundreds of financial institutions across 40 countries and more than 10 million brokerage accounts through institutional-grade APIs. Its 400 plus team members work remotely from their favorite places around the world, with teammates spanning the USA, Canada, Japan, Hungary, Nigeria, Brazil, the UK and beyond. Alpaca is hiring a Staff Analytics Engineer to own and execute the vision for its data transformation layer. The role sits at the heart of a data platform that processes hundreds of millions of events daily from transactional databases, API logs, CRMs, payment systems and marketing platforms. In the company's own words, you will join our 100% remote team and work closely with Data Engineers, Data Scientists and business users, using dbt and Trino on a GCP-based open-source data stack to build robust, scalable data models delivered through BI tools, reports and reverse ETL. The posting is listed on Alpaca's Greenhouse board with the location Remote - EMEA, so it is open to candidates across Europe, the Middle East and Africa rather than a single country. Compensation is described as a competitive salary plus stock options with health benefits, a one-time 500 USD home-office setup and a 150 USD monthly stipend via Brex card; no salary range is published. Published on Alpaca's Greenhouse board on 24 September 2026.
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Own the transformation layer: design, build and maintain scalable data models using dbt and SQL to support needs ranging from monthly financial reporting to near-real-time operational metrics. Set technical standards for data modelling, development, testing and monitoring so data quality, cent-level integrity and discoverability hold up. Enable stakeholders in finance, operations, customer success and marketing by understanding their requirements and delivering reliable data products. Create repeatable patterns for integrating data models with BI tools and reverse ETL processes for consistent metric reporting. Champion robust change management, source control, code reviews and data monitoring as products and data evolve.
4 plus years of experience in analytics engineering or data engineering with a strong focus on transformation in ELT. Proven track record of owning data products end to end with strong data quality, scalability and robust data models. Comfortable with ambiguity, able to define requirements with stakeholders and take ownership with minimal oversight in a fast-paced environment. Experience proactively improving data warehouse performance and ETL efficiency. Expert-level SQL and dbt, proficiency in Python, hands-on query optimization across OLTP and OLAP systems such as Postgres and Iceberg, semantic layer modelling (Cube or dbt Semantic Layer), ownership of CI/CD workflows and Git-based standards, and familiarity with GCP or AWS. Nice to have: Airbyte, Airflow, and brokerage or financial-markets domain experience.
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This job title typically pays $169,290 to $204,000 a year (median $186,645) for similar roles in the US.
Estimate from US Bureau of Labor Statistics data, not provided by the employer.
